RigolScopeSansVISATesting.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\\title{Prototype and Trial programming of a LXI scope with Python Socket library without VISA}\n",
    "\\author{Steven K Armour}\n",
    "\\maketitle"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# References\n",
    "+ Python for LXI Instrument Control by Eric Jacobson http://gpete.blogs.keysight.com/2015/07/python-for-lxi-instrument-control.html\n",
    "\n",
    "+ Rigol MSO1000Z/DS1000Z Series Digital Oscilloscope Programming Guide http://int.rigol.com/File/TechDoc/20151218/MSO1000Z&DS1000Z_ProgrammingGuide_EN.pdf\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Libraries that are needed\n",
    "import socket #library that will do the connection between computer and LXI inst\n",
    "import time #used to pause program to handle non asynchronous actions\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import pickle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "class ScopeSocket():\n",
    "    \"\"\"\n",
    "    Prototype class for establishing computer to scope connection via socket \n",
    "    (IP4) programming via the SCPI LXI protocol\n",
    "    \n",
    "    \"\"\"\n",
    "    def __init__(self, ScopeIP, ScopePort):\n",
    "        \"\"\"\n",
    "        initlizes the class instincince\n",
    "        \n",
    "        Args:\n",
    "            ScopeIP (str): the IP address of the target scope\n",
    "            ScopePort (str): the socket port on the scope \n",
    "            ex Rigol DS scopes use 5555\n",
    "        \n",
    "        \"\"\"\n",
    "        #bind the IP and Port to the object\n",
    "        self.ScopeIP=ScopeIP; self.ScopePort=ScopePort\n",
    "    \n",
    "    def SocketInit(self, TimeOutSec=3.0):\n",
    "        \"\"\"\n",
    "        Method to startup the socket interconnect\n",
    "        \n",
    "        Args:\n",
    "            None\n",
    "            \n",
    "        Note:\n",
    "            good intro to sockets: \n",
    "            http://www.pythonforbeginners.com/code-snippets-source-code/port-scanner-in-python\n",
    "        \"\"\"\n",
    "        # create socket instance in the class that is a streaming IP4\n",
    "        self.s=socket.socket(socket.AF_INET, socket.SOCK_STREAM)\n",
    "        # set socket options\n",
    "        self.s.setsockopt(socket.IPPROTO_TCP, socket.TCP_NODELAY, 0)\n",
    "        \n",
    "        self.s.settimeout(TimeOutSec)\n",
    "        \n",
    "        #make the connection to the scope\n",
    "        self.s.connect((self.ScopeIP, self.ScopePort))\n",
    "    \n",
    "    def SocketClose(self):\n",
    "        \"\"\"\n",
    "        Method for closeing the socket (IP4) connection\n",
    "        Args:\n",
    "            None\n",
    "        \"\"\"\n",
    "        self.s.close()\n",
    "        print('Scope Socket Closed')\n",
    "    \n",
    "    def Command(self, cmd):\n",
    "        \"\"\"\n",
    "        Convince  Method to pass SCPI commands over the socket such that for\n",
    "        Rigol scopes the command is auto ended with a '\\n' and is encoded to \n",
    "        Ascii bit and send on the socket connection. Most useful is sending\n",
    "        commands and not quarries \n",
    "        \n",
    "        Args:\n",
    "            cmd (str): SCPI command to be sent needs to be in all caps\n",
    "            example '*RST' will reset the scope; see the programing guide\n",
    "        \"\"\"\n",
    "        cmd=f'{cmd}\\n'\n",
    "        self.s.sendall(cmd.encode())\n",
    "    \n",
    "    def Responce(self, resBitLen=12):\n",
    "        \"\"\"\n",
    "        Convince Method for reciving the response of a quarry from the scope.\n",
    "        This methods return returns the raw retrived bit \n",
    "        \n",
    "        Args:\n",
    "            resBitLen (int): the N in 2^N to specify the returned informtion \n",
    "            package\n",
    "        \n",
    "        Returns:\n",
    "            returns the response information from the scope as is\n",
    "        \"\"\"\n",
    "        return self.s.recv(2**resBitLen)\n",
    "    \n",
    "    def Quarry(self, cmd, resBitLen=12, Ascii=True):\n",
    "        \"\"\"\n",
    "        Convince Method for sending qurry (ask for -> receive) commands that\n",
    "        will send the SCPI commands and automatically get the responce from\n",
    "        the scope and will return the result \n",
    "        \n",
    "        Args:\n",
    "            cmd (str): SCPI command to be sent needs to be in all caps\n",
    "            example '*IDN?' will ask the scope for its IDN number; \n",
    "            see the programing guide\n",
    "            \n",
    "            resBitLen (int): the N in 2^N to specify the returned informtion \n",
    "            package\n",
    "            \n",
    "            Ascii (bool:Default True): if True will try to return the response\n",
    "            from the Quarry as a string assuming \"utf-8\" ascii decoding\n",
    "        \n",
    "        Returns:\n",
    "            str from decoded response if Arg Ascii is True \n",
    "            \n",
    "            raw response of Arg Ascii is False\n",
    "        \n",
    "        \"\"\"\n",
    "        #prep and send command\n",
    "        cmd=f'{cmd}\\n'\n",
    "        self.s.sendall(cmd.encode())\n",
    "        \n",
    "        # get the response\n",
    "        res=self.s.recv(2**resBitLen)\n",
    "        \n",
    "        if Ascii:\n",
    "            # attempt at byte to 'utf-8' decoding\n",
    "            try:\n",
    "                if res.decode('utf-8')=='command error':\n",
    "                    print(f'Command: \"{cmd}\" is invalaid')\n",
    "                else:\n",
    "                    return res\n",
    "            except:\n",
    "                pass\n",
    "        else:\n",
    "            return res\n",
    "            \n",
    "\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Begin Testing\n",
    "\n",
    "## Test setup:\n",
    "The testing for a analog signal  input to the scope was done via a sine wave from a generic benchtop signal generator connected to the scopes Channel 1 with all other channels left open"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Connection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "ScopeIP=\"192.168.2.5\"\n",
    "#Supnet:255, 255 0\n",
    "ScopePort = 5555"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "Rigol=ScopeSocket(ScopeIP, ScopePort)\n",
    "Rigol.SocketInit()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Confirm with IDN grap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "b'RIGOL TECHNOLOGIES,DS1104Z,DS1ZA173719352,00.04.03.SP1\\n'"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Rigol.Quarry('*IDN?')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Command: \"IDN?\n",
      "\" is invalaid\n"
     ]
    }
   ],
   "source": [
    "#test bad quarry\n",
    "Rigol.Quarry('IDN?')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Running Commands\n",
    "pg 17"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "#auto scetup command\n",
    "Rigol.Command('AUT')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "Rigol.Command('STOP')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "Rigol.Command('RUN')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "Rigol.Command('STOP')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "#clear the reading from the screen\n",
    "Rigol.Command('CLE')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "#do a signle measurment\n",
    "Rigol.Command('SING')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Measurment Commands"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "b'9.9E37\\n'"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Meausre qurry command,  what is being measured, where is the measuement from\n",
    "#page 141\n",
    "\n",
    "#Ch2 was not connected\n",
    "Rigol.Quarry('MEAS:ITEM? VMAX, CHAN2') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "b'2.360000e+01\\n'"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Meausre qurry command,  what is being measured, where is the measuement from\n",
    "\n",
    "#Ch1 connected to sine genrator\n",
    "Rigol.Quarry('MEAS:ITEM? VMAX, CHAN1') "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Math Commands"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Set up the scopes FFT\n",
    "Rigol.Command('MATH:FFT:SOUR:CHAN1')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Disapley the FFT on the scope display\n",
    "Rigol.Command('MATH:DISP ON')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Turn off disapley the FFT on the scope display\n",
    "Rigol.Command('MATH:DISP OFF')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Wavefrom acustion"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### ASCII acqusisiton"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# set output to be ascii bit encodeing; pg 234\n",
    "Rigol.Command('WAV:FORM ASC')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# tell it the source of the waveform; pg 233\n",
    "Rigol.Command('WAV:SOUR CHAN1')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# tell it how to get the wave form; pg 234\n",
    "Rigol.Command('WAV:MODE NORM')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "b'2,0,1200,1,5.000000e-06,-3.000000e-03,0,2.000000e-01,-44,127\\n'"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#grap the preamble ; pg 242\n",
    "Preamble=Rigol.Quarry('WAV:PRE?', 16); Preamble"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'2,0,1200,1,5.000000e-06,-3.000000e-03,0,2.000000e-01,-44,127\\n'"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Preamble=Preamble.decode('utf-8'); Preamble"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Parm</th>\n",
       "      <th>Value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>format</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>type</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>points</td>\n",
       "      <td>1200.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>count</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>xincrement</td>\n",
       "      <td>0.000005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>xorigin</td>\n",
       "      <td>-0.003000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>xreference</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>yincrement</td>\n",
       "      <td>0.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>yorigin</td>\n",
       "      <td>-44.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>yreference</td>\n",
       "      <td>127.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Parm        Value\n",
       "0      format     2.000000\n",
       "1        type     0.000000\n",
       "2      points  1200.000000\n",
       "3       count     1.000000\n",
       "4  xincrement     0.000005\n",
       "5     xorigin    -0.003000\n",
       "6  xreference     0.000000\n",
       "7  yincrement     0.200000\n",
       "8     yorigin   -44.000000\n",
       "9  yreference   127.000000"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "PreambleDF=pd.DataFrame(columns=['Parm', 'Value'])\n",
    "PreambleDF['Parm']=['format', 'type', 'points', 'count', \n",
    "                    'xincrement', 'xorigin', 'xreference', \n",
    "                    'yincrement', 'yorigin', 'yreference']\n",
    "PreambleDF['Value']=[float(i) for i  in Preamble.split(',')]\n",
    "PreambleDF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "b'#90000159286.799988e+00,8.599987e+00,7.599988e+00,8.999987e+00,8.199987e+00,9.599986e+00,8.599987e+00,1.019999e+01,9.199986e+00,1.099998e+01,9.799986e+00,1.159998e+01,1.059999e+01,1.219998e+01,1.119998e+01,1.279998e+01,1.159998e+01,1.319998e+01,1.219998e+01,1.379998e+01,1.279998e+01,1.439998e+01,1.339998e+01,1.479998e+01,1.399998e+01,1.519998e+01,1.439998e+01,1.579998e+01,1.479998e+01,1.659998e+01,1.539998e+01,1.679998e+01,1.579998e+01,1.719998e+01,1.619998e+01,1.779999e+01,1.659998e+01,1.839999e+01,1.739998e+01,1.859999e+01,1.779999e+01,1.939999e+01,1.799999e+01,1.959999e+01,1.859999e+01,1.999999e+01,1.899999e+01,2.020000e+01,1.939999e+01,2.080000e+01,1.979999e+01,2.120000e+01,2.120000e+01,1.999999e+01,2.020000e+01,2.160000e+01,2.060000e+01,2.200000e+01,2.080000e+01,2.220000e+01,2.120000e+01,2.240000e+01,2.120000e+01,2.260000e+01,2.140000e+01,2.280000e+01,2.160000e+01,2.300001e+01,2.180000e+01,2.300001e+01,2.200000e+01,2.320001e+01,2.320001e+01,2.200000e+01,2.220000e+01,2.340001e+01,2.220000e+01,2.340001e+01,2.220000e+01,2.340001e+01,2.360001e+01,2.220000e+01,2.340001e+01,2.200000e+01,2.320001e+01,2.220000e+01,2.320001e+01,2.200000e+01,2.200000e+01,2.320001e+01,2.160000e+01,2.320001e+01,2.280000e+01,2.160000e+01,2.280000e+01,2.140000e+01,2.260000e+01,2.140000e+01,2.220000e+01,2.100000e+01,2.220000e+01,2.080000e+01,2.200000e+01,2.060000e+01,2.160000e+01,2.040000e+01,2.120000e+01,1.999999e+01,2.120000e+01,1.959999e+01,2.080000e+01,1.9399'"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#grap the wavefrom from the screen; pg 235\n",
    "Data1=Rigol.Quarry('WAV:DATA?', 32)\n",
    "Data1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Data2=Rigol.Responce(32); Data2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Need to get time out working\n",
    "#Data3=Rigol.Responce(32); Data3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Data1==Data2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Need to figure out the call sizes and how to clear the output buffer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Data=Data1.decode('utf-8')+Data2.decode('utf-8'); Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#strip of leading 11 junk and traling new line\n",
    "Data=Data[11:-1]; Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 6.799988,  8.599987,  7.599988, ...,  8.999987,  7.799987,\n",
       "        9.599986])"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Data=np.array([float(i) for i in Data.split(',')])\n",
    "Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(         Parm        Value\n",
       " 0      format     2.000000\n",
       " 1        type     0.000000\n",
       " 2      points  1200.000000\n",
       " 3       count     1.000000\n",
       " 4  xincrement     0.000005\n",
       " 5     xorigin    -0.003000\n",
       " 6  xreference     0.000000\n",
       " 7  yincrement     0.200000\n",
       " 8     yorigin   -44.000000\n",
       " 9  yreference   127.000000, 1200)"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "PreambleDF, len(Data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.0, 0.0059950000000000003)"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x=np.arange(0, (1200)*0.000005, 0.000005)\n",
    "x[0], x[-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f140d1b07f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "DataAscii=pd.DataFrame(columns=['t', 'V'])\n",
    "DataAscii['t']=x; DataAscii['V']=Data\n",
    "DataAscii.plot(x='t', y='V')\n",
    "plt.grid()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "PreambleDF.to_pickle('asciiPreamble.p')\n",
    "DataAscii.to_pickle('asciiData.p')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### byte"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### WORD"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Decode rs-232 command *IDN?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "author": "Prototype and Trial programming of a LXI scope with Python Socket library without VISA",
  "hide_input": false,
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  },
  "latex_envs": {
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   "current_citInitial": 1,
   "eqLabelWithNumbers": true,
   "eqNumInitial": 1,
   "hotkeys": {
    "equation": "Ctrl-E",
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   "labels_anchors": false,
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   "user_envs_cfg": false
  },
  "toc": {
   "nav_menu": {},
   "number_sections": true,
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   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}